AI-Driven Financial Intelligence
We build machine learning and language model applications for risk, pricing, portfolio and client decisions.
Early warning and anomaly detection
Anticipating movements in prices, spreads, currencies and credit exposures, and identifying the reasons behind them.
Early warning and anomaly detection
Anticipating movements in prices, spreads, currencies and credit exposures, and identifying the reasons behind them.
- Detection of unusual movements in yields, spreads, prices and currency pairs
- News, research and central bank commentary read alongside the move to identify the cause
- Short-horizon forecasts expressed as a range of outcomes with a confidence level
- Indirect exposure identified from filings, supply chain data and balance sheet positions
- Early warning signals on credit portfolios covering the borrower and its counterparties
- Coverage extended to unrated and non-traded companies through comparable peers
Pricing and calibration
Machine learning models that produce indicative prices and risk sensitivities for derivatives, exotics and structured products.
Pricing and calibration
Machine learning models that produce indicative prices and risk sensitivities for derivatives, exotics and structured products.
- Model-calibrated volatility surfaces for pricing exotic structures
- Machine learning pricing engines for indicative prices and Greeks, with full simulation retained for final confirmation
- Scenario engines running large simulation sets
- Market regime classification with a forward view on volatility
Optimisation within regulatory constraints
Engines that optimise within the limits a regulated institution operates under.
Optimisation within regulatory constraints
Engines that optimise within the limits a regulated institution operates under.
- RWA, LCR, NSFR, VaR, capital and IFRS 9 hedge effectiveness built into the problem definition
- Signals drawn from market and quantitative data, machine learning and text
- Objective set by the client: return on capital, spread, payoff or capital consumption
- Continuous adjustment as positions and markets move
- The business sets the objective, risk sets the limits and the engine proposes rather than executes
- Output is a list of actions with supporting reasoning and a before-and-after comparison
Behavioural and client analytics
AI and machine learning applied to segmentation, price sensitivity and execution probability, across FX, lending, cards, deposits and other products.
Behavioural and client analytics
AI and machine learning applied to segmentation, price sensitivity and execution probability, across FX, lending, cards, deposits and other products.
- Clients grouped into behavioural segments from executed transactions
- Price sensitivity and likelihood of execution estimated by segment and market condition
- Market basket and affinity analysis to identify product adjacencies and cross-sell opportunities
- Pricing frameworks built on cost, market and customer-value layers, with guardrails and negotiation thresholds
- Pricing dispersion, discounts, waivers and revenue leakage tracked by segment and relationship
- Client-level reports combining segment, activity profile and suggested approach
- Used for pricing strategy, coverage prioritisation and product recommendation
Document intelligence and agents
Systems that answer plain-language questions across documents and databases, and run processes end to end.
Document intelligence and agents
Systems that answer plain-language questions across documents and databases, and run processes end to end.
- Questions asked in ordinary language, with the system writing the query so figures come from the data itself
- Answers drawn across multiple documents at once including research, credit files, contracts and regulation
- Plain-language rationale and risk caveats generated alongside the answer
- Term sheets, reports and memos drafted from model output
- Agents that run a process unattended, with exceptions raised for review
- Continuous monitoring with breaches flagged as they occur and a proposed remedy attached
- Used for hedge effectiveness monitoring, due diligence, research surveillance and geopolitical exposure tracking
- Arabic and English across the full pipeline, built for GCC banking and Islamic finance
- Runs on local models where data cannot leave the institution
How we work
Define the decision to improve; build against your data; test for accuracy, stability and explainability; and deploy, monitor and retrain.
We are model agnostic. Proprietary, open and commercial models are selected per task and routed by language, complexity and sensitivity, including on-premise models for confidential work. Explainability and audit trails are built in from the start.
These capabilities combine into domain engines. Market data, text and the institution's own portfolio and client data feed a set of models covering forecasting, pricing, exposure detection and recommendation, delivered through a view built for each user group and output ready to go to the client.
Who it's for
Banks, Asset managers, Insurers, Corporate treasury, Private credit & PE, Family offices
Packaged versions of these engines are listed under Solutions.